Considerations on the use of microsensors to profile dissolved H2 concentrations in microbial electrochemical reactors.

Measuring the distribution and dynamics of H2 in microbial electrochemical reactors is valuable to gain insights into the processes behind novel bioelectrochemical technologies, such as microbial electrosynthesis. Here, a microsensor method to measure and profile dissolved H2 concentrations in standard H-cell reactors is described. Graphite cathodes were oriented horizontally to enable the use of a motorized microprofiling system and a stereomicroscope was used to place the H2 microsensor precisely on the cathode surface. Profiling was performed towards the gas-liquid interface, while preserving the electric connections and flushing the headspace (to maintain anoxic conditions) and under strict temperature control (to overcome the temperature sensitivity of the microsensors). This method was tested by profiling six reactors, with and without inoculation of the acetogen Sporomusa ovata, at three different time points. H2 accumulated over time in the abiotic controls, while S. ovata maintained low H2 concentrations throughout the liquid phase (< 4 µM) during the whole experimental period. These results demonstrate that this setup generated insightful H2 profiles. However, various limitations of this microsensor method were identified, as headspace flushing lowered the dissolved H2 concentrations over time. Moreover, microsensors can likely not accurately measure H2 in the immediate vicinity of the solid cathode, because the solids cathode surface obstructs H2 diffusion into the microsensor. Finally, the reactors had to be discarded after microsensor profiling. Interested users should bear these considerations in mind when applying microsensors to characterize microbial electrochemical reactors.

Cable Bacteria Skeletons as Catalytically Active Electrodes.

Cable bacteria are multicellular, filamentous bacteria that use internal conductive fibers to transfer electrons over centimeter distances from donors within anoxic sediment layers to oxygen at the surface. We extracted the fibers and used them as free-standing bio-based electrodes to investigate their electrocatalytic behavior. The fibers catalyzed the reversible interconversion of oxygen and water, and an electric current was running through the fibers even when the potential difference was generated solely by a gradient of oxygen concentration. Oxygen reduction as well as oxygen evolution were confirmed by optical measurements. Within living cable bacteria, oxygen reduction by direct electrocatalysis on the fibers and not by membrane-bound proteins readily explains exceptionally high cell-specific oxygen consumption rates observed in the oxic zone, while electrocatalytic water oxidation may provide oxygen to cells in the anoxic zone.

Optical sensors (optodes) for multiparameter chemical imaging: classification, challenges, and prospects.

Chemical gradients and uneven distribution of analytes are common in natural and artificial systems. As a result, the ability to visualize chemical distributions in two or more dimensions has gained significant importance in recent years. This has led to the integration of chemical imaging techniques into all domains of analytical chemistry. In this review, we focus on the use of optical sensors, so-called optodes, to obtain real-time and multidimensional images of two or more parameters simultaneously. It is important to emphasize that multiparameter imaging in this context is not confined solely to multiple chemical parameters (analytes) but also encompasses physical (e.g., temperature or flow) or biological (e.g., metabolic activity) parameters. First, we discuss the technological milestones that have paved the way for chemical imaging using optodes. Later, we delve into various strategies that can be taken to enable multiparameter imaging. The latter spans from developing novel receptors that enable the recognition of multiple parameters to chemometrics and machine learning-based techniques for data analysis. We also explore ongoing trends, challenges, and prospects for future developments in this field. Optode-based multiparameter imaging is a rapidly expanding field that is being fueled by cutting-edge technologies. Chemical imaging possesses the potential to provide novel insights into complex samples, bridging not only across various scientific disciplines but also between research and society.

Timing matters: the overlooked issue of response time mismatch in pH-dependent analyte sensing using multiple sensors.

Accurate measurement of pH-dependent analytes is crucial for a wide range of applications, including environmental monitoring, industrial processes, and healthcare diagnostics. In multi-sensor systems, combining data from multiple sensors offers the potential for more comprehensive analysis, yet it is important to be aware of the limitations of this approach. In this paper, we investigate the often-overlooked issue of response time mismatch among sensors, which can introduce significant errors in calculated sum parameters. We present a model and software application (SensinSilico) that allows predicting the error arising from a mismatch of sensor response times. The model was compared and validated using experimental results from calculations of total dissolved sulphide (TDS). These calculations were based on data from concurrent sensor measurements of hydrogen sulfide (H2S) and pH, which had different response times. We believe that SensinSilico has the potential to be a powerful tool for researchers, professionals, and end-users, enabling them to estimate and minimize errors arising from response time mismatches, enhancing the accuracy and reliability of their results.

Differential impacts of sewage sludge and biochar on phosphorus-related processes: An imaging study of the rhizosphere.

Recycling of phosphorus (P) from waste streams in agriculture is essential to reduce the negative environmental effects of surplus P and the unsustainable mining of geological P resources. Sewage sludge (SS) is an important P source; however, several issues are associated with the handling and application of SS in agriculture. Thus, post-treatments such as pyrolysis of SS into biochar (BC) could address some of these issues. Here we elucidate how patches of SS in soil interact with the living roots of wheat and affect important P-related rhizosphere processes compared to their BC counterparts. Wheat plants were grown in rhizoboxes with sandy loam soil, and 1 cm Ø patches with either SS or BC placed 10 cm below the seed. A negative control (CK) was included. Planar optode pH sensors were used to visualize spatiotemporal pH changes during 40 days of plant growth, diffusive gradients in thin films (DGT) were applied to map labile P, and zymography was used to visualize the spatial distribution of acid (ACP) and alkaline (ALP) phosphatase activity. In addition, bulk soil measurements of available P, pH, and ACP activity were conducted. Finally, the relative abundance of bacterial P-cycling genes (phoD, phoX, phnK) was determined in the patch area rhizosphere. Labile P was only observed in the area of the SS patches, and SS further triggered root proliferation and increased the activity of ACP and ALP in interaction with the roots. In contrast, BC seemed to be inert, had no visible effect on root growth, and even reduced ACP and ALP activity in the patch area. Furthermore, there was a lower relative abundance of phoD and phnK genes in the BC rhizosphere compared to the CK. Hence, optimization of BC properties is needed to increase the short-term efficiency of BC from SS as a P fertilizer.

Let's Talk about Slime; or Why Biofouling Needs More Attention in Sensor Science.

Although there is a growing demand for new sensors for environmental monitoring, biofouling continues to plague current sensors and sensing networks. As soon as a sensor is placed in water, the formation of a biofilm begins. Once a biofilm is established, reliable measurements are often no longer possible. Although current biofouling mitigation strategies can slow the biofouling process, a biofilm will eventually develop on or near the sensing surface. While antibiofouling strategies are being continuously developed, the complexity of the biofilm community structure and the surrounding environment means that there is unlikely to be a single solution that will minimize biofilms on all environmental sensors. Thus, antibiofouling research often focuses on optimizing a specific biofilm mitigation approach for a given sensor, application, and environmental condition. While this is practical from the standpoint of a sensor developer, it makes the comparison of different mitigation strategies difficult. In this Perspective, we discuss the application of different biofouling mitigation strategies to sensing and then explore the need for the sensor community to adopt standard protocols to increase the comparability of the biofouling mitigation approaches and help sensor developers identify the most appropriate strategy for their system.

Imaging of CO2 and Dissolved Inorganic Carbon via Electrochemical Acidification-Optode Tandem.

Dissolved inorganic carbon (DIC) is a key component of the global carbon cycle and plays a critical role in ocean acidification and proliferation of phototrophs. Its quantification at a high spatial resolution is essential for understanding various biogeochemical processes. We present an analytical method for 2D chemical imaging of DIC by combining a conventional CO2 optode with localized electrochemical acidification from a polyaniline (PANI)-coated stainless-steel mesh electrode. Initially, the optode response is governed by local concentrations of free CO2 in the sample, corresponding to the established carbonate equilibrium at the (unmodified) sample pH. Upon applying a mild potential-based polarization to the PANI mesh, protons are released into the sample, shifting the carbonate equilibrium toward CO2 conversion (>99%), which corresponds to the sample DIC. It is herein demonstrated that the CO2 optode-PANI tandem enables the mapping of free CO2 (before PANI activation) and DIC (after PANI activation) in complex samples, providing high 2D spatial resolution (approx. 400 µm). The significance of this method was proven by inspecting the carbonate chemistry of complex environmental systems, including the freshwater plant Vallisneria spiralis and lime-amended waterlogged soil. This work is expected to pave the way for new analytical strategies that combine chemical imaging with electrochemical actuators, aiming to enhance classical sensing approaches via in situ (and reagentless) sample treatment. Such tools may provide a better understanding of environmentally relevant pH-dependent analytes related to the carbon, nitrogen, and sulfur cycles.

Reducing biofouling on optical oxygen sensors; a simple modification enabling sensor cleaning via water splitting.

Biofouling is a major challenge in environmental sensing. Current mitigation strategies are often expensive, energy consuming or require toxic chemicals. In this contribution electrochemical biofouling control is evaluated as an alternative approach to reduce biofouling on an optical O2 sensor (optode). By using the outer stainless-steel sleeve of the optode as an electrode, water splitting increases the local pH and forms H2 bubbles close to the optode surface. As seen in a biofouling assay, the combination of those processes leads to biofilm removal when compared to a non-modified optode. The findings suggest that electrochemical biofouling control can be an attractive, low-cost alternative to current biofouling mitigation strategies and that this approach may not be limited to O2 optodes.

Machine learning for optical chemical multi-analyte imaging : Why we should dare and why it's not without risks.

Simultaneous sensing of metabolic analytes such as pH and O2 is critical in complex and heterogeneous biological environments where analytes often are interrelated. However, measuring all target analytes at the same time and position is often challenging. A major challenge preventing further progress occurs when sensor signals cannot be directly correlated to analyte concentrations due to additional effects, overshadowing and complicating the actual correlations. In fields related to optical sensing, machine learning has already shown its potential to overcome these challenges by solving nested and multidimensional correlations. Hence, we want to apply machine learning models to fluorescence-based optical chemical sensors to facilitate simultaneous imaging of multiple analytes in 2D. We present a proof-of-concept approach for simultaneous imaging of pH and dissolved O2 using an optical chemical sensor, a hyperspectral camera for image acquisition, and a multi-layered machine learning model based on a decision tree algorithm (XGBoost) for data analysis. Our model predicts dissolved O2 and pH with a mean absolute error of < 4.50·10-2 and < 1.96·10-1, respectively, and a root mean square error of < 2.12·10-1 and < 4.42·10-1, respectively. Besides the model-building process, we discuss the potentials of machine learning for optical chemical sensing, especially regarding multi-analyte imaging, and highlight risks of bias that can arise in machine learning-based data analysis.

Optode-based chemical imaging of laboratory burned soil reveals millimeter-scale heterogeneous biogeochemical responses.

Soil spatial responses to fire are unclear. Using optical chemical sensing with planar 'optodes', pH and dissolved O2 concentration were tracked spatially with a resolution of 360 µm per pixel for 72 h after burning soil in the laboratory with a butane torch (∼1300 °C) and then sprinkling water to simulate a postfire moisture event. Imaging data from planar optodes correlated with microbial activity (quantified via RNA transcripts). Post-fire and post-wetting, soil pH increased throughout the entire ∼13 cm × 17 cm × 20 cm rectangular cuboid of sandy loam soil. Dissolved O2 concentrations were not impacted until the application of water postfire. pH and dissolved O2 both negatively correlated (p < 0.05) with relative transcript expression for galactose metabolism, the degradation of aromatic compounds, sulfur metabolism, and narH. Additionally, dissolved O2 negatively correlated (p < 0.05) with the relative activity of carbon fixation pathways in Bacteria and Archaea, amoA/amoB, narG, nirK, and nosZ. nifH was not detected in any samples. Only amoB and amoC correlated with depth in soil (p < 0.05). Results demonstrate that postfire soils are spatially complex on a mm scale and that using optode-based chemical imaging as a chemical navigator for RNA transcript sampling is effective.

Microsensor for total dissolved sulfide (TDS).

Total Dissolved Sulfide (TDS) concentrations can either be derived from simultaneous measurement of pH and one of the sulfide species or determined indirectly in samples following an acidification step. Here we report a microsensor that allows for direct measurement of TDS in aquatic media without the need for pH monitoring. An acidic chamber placed in front of a commercial, amperometric H2S microsensor allows for the in-situ conversion of dissolved ionic sulfide species to H2S, which in turn is oxidized at the transducer anode. A typical sensor had a tip opening of 30 µm, a response time of <50 s and linear range between 0.5 and 650 µM. The sensor performance can be largely tuned by altering the geometry of the chamber. Sensors of different sensitivity (0.04-2.93 pA/µM) showed no noticeable change in zero current and sensitivity during continuous polarization over 7 weeks. The sensor was successfully applied to resolve microscale TDS gradients in freshwater and marine sediments. Other avenues of application include the online monitoring of industrial and urban sewers.

Imaging Sample Acidification Triggered by Electrochemically Activated Polyaniline.

In this letter, we demonstrate 2D acidification of samples at environmental and physiological pH with an electrochemically activated polyaniline (PANI) mesh. A novel sensor-actuator concept is conceived for such a purpose. The sample is sandwiched between the PANI (actuator) and a planar pH optode (sensor) placed at a very close distance (∼0.50 mm). Upon application of a mild potential to the mesh, in contrast to previously reported acidification approaches, PANI releases a significant number of protons, causing an acid-base titration in the sample. This process is monitored in time and space by the pH optode, providing chemical imaging of the pH decrease along the dynamic titration via photographic acquisition. Acidification of samples at varying buffer capacity has been investigated: the higher the buffer capacity, the more time (and therefore proton charge) was needed to reach a pH of 4.5 or even lower. Also, the ability to map spatial differences in buffer capacity within a sample during the acid-base titration was unprecedentedly proven. The sensor-actuator concept could be used for monitoring certain analytes in samples that specifically require acidification pretreatment. Particularly, in combination with different optodes, dynamic mapping of concentration gradients will be accessible in complex environmental samples ranging from roots and sediments to bacterial aggregates.

Ciliary flows in corals ventilate target areas of high photosynthetic oxygen production.

Most tropical corals live in symbiosis with Symbiodiniaceae algae whose photosynthetic production of oxygen (O2) may lead to excess O2 in the diffusive boundary layer (DBL) above the coral surface. When flow is low, cilia-induced mixing of the coral DBL is vital to remove excess O2 and prevent oxidative stress that may lead to coral bleaching and mortality. Here, we combined particle image velocimetry using O2-sensitive nanoparticles (sensPIV) with chlorophyll (Chla)-sensitive hyperspectral imaging to visualize the microscale distribution and dynamics of ciliary flows and O2 in the coral DBL in relation to the distribution of Symbiodiniaceae Chla in the tissue of the reef building coral, Porites lutea. Curiously, we found an inverse relation between O2 in the DBL and Chla in the underlying tissue, with patches of high O2 in the DBL above low Chla in the underlying tissue surrounding the polyp mouth areas and pockets of low O2 concentrations in the DBL above high Chla in the coenosarc tissue connecting neighboring polyps. The spatial segregation of Chla and O2 is related to ciliary-induced flows, causing a lateral redistribution of O2 in the DBL. In a 2D transport-reaction model of the coral DBL, we show that the enhanced O2 transport allocates parts of the O2 surplus to areas containing less chla, which minimizes oxidative stress. Cilary flows thus confer a spatially complex mass transfer in the coral DBL, which may play an important role in mitigating oxidative stress and bleaching in corals.

Simultaneous visualization of flow fields and oxygen concentrations to unravel transport and metabolic processes in biological systems.

From individual cells to whole organisms, O2 transport unfolds across micrometer- to millimeter-length scales and can change within milliseconds in response to fluid flows and organismal behavior. The spatiotemporal complexity of these processes makes the accurate assessment of O2 dynamics via currently available methods difficult or unreliable. Here, we present "sensPIV," a method to simultaneously measure O2 concentrations and flow fields. By tracking O2-sensitive microparticles in flow using imaging technologies that allow for instantaneous referencing, we measured O2 transport within (1) microfluidic devices, (2) sinking model aggregates, and (3) complex colony-forming corals. Through the use of sensPIV, we find that corals use ciliary movement to link zones of photosynthetic O2 production to zones of O2 consumption. SensPIV can potentially be extendable to study flow-organism interactions across many life-science and engineering applications.

Noise versus Resolution in Optical Chemical Imaging-How Reliable Are Our Measurements?

Optical chemical imaging has established itself as a valuable technique for visualizing analyte distributions in 2D, notably in medical, biological, and environmental applications. In particular for image acquisitions on small scales between few millimeter to the micrometer range, as well as in heterogeneous samples with steep analyte gradients, image resolution is essential. When individual pixels are inspected, however, image noise becomes a metric as relevant as image accuracy and precision, and denoising filters are applied to preserve relevant information. While denoising filters smooth the image noise, they can also lead to a loss of spatial resolution and thus to a loss of relevant information about analyte distributions. To investigate the trade-off between image resolution and noise reduction for information preservation, we studied the impact of random camera noise and noise due to incorrect camera settings on oxygen optodes using the ratiometric imaging technique. First, we estimated the noise amplification across the calibration process using a Monte Carlo simulation for nonlinear fit models. We demonstrated how initially marginal random camera noise results in a significant standard deviation (SD) for oxygen concentration of up to 2.73% air under anoxic conditions, although the measurement was conducted under ideal conditions and over 270 thousand sample pixels were considered during calibration. Second, we studied the effect of the Gaussian denoising filter on a steep oxygen gradient and investigated the impact when the smoothing filter is applied during data processing. Finally, we demonstrated the effectiveness of a Savitzky-Golay filter compared to the well-established Gaussian filter.

Metabolic Profiling of Interspecies Interactions During Sessile Bacterial Cultivation Reveals Growth and Sporulation Induction in Paenibacillus amylolyticus in Response to Xanthomonas retroflexus.

The toolbox available for microbiologists to study interspecies interactions is rapidly growing, and with continuously more advanced instruments, we are able to expand our knowledge on establishment and function of microbial communities. However, unravelling molecular interspecies interactions in complex biological systems remains a challenge, and interactions are therefore often studied in simplified communities. Here we perform an in-depth characterization of an observed interspecies interaction between two co-isolated bacteria, Xanthomonas retroflexus and Paenibacillus amylolyticus. Using microsensor measurements for mapping the chemical environment, we show how X. retroflexus promoted an alkalization of its local environment through degradation of amino acids and release of ammonia. When the two species were grown in proximity, the modified local environment induced a morphological change and growth of P. amylolyticus followed by sporulation. 2D spatial metabolomics enabled visualization and mapping of the degradation of oligopeptide structures by X. retroflexus and morphological changes of P. amylolyticus through e.g. the release of membrane-associated metabolites. Proteome analysis and microscopy were used to validate the shift from vegetative growth towards sporulation. In summary, we demonstrate how environmental profiling by combined application of microsensor, microscopy, metabolomics and proteomics approaches can reveal growth and sporulation promoting effects resulting from interspecies interactions.

Total Dissolved Inorganic Carbon Sensor Based on Amperometric CO2 Microsensor and Local Acidification.

We present a dipping probe total dissolved inorganic carbon (DIC) microsensor based on a localized acidic microenvironment in front of an amperometric CO2 microsensor. The acidic milieu facilitates conversion of bicarbonate and carbonate to CO2, which in turn is reduced at a silver cathode. Interfering oxygen is removed by an acidic CrCl2 oxygen trap. Theoretical simulations of microsensor functioning were performed to find a suitable compromise between response time and near-complete conversion of bicarbonate to CO2. The sensor exhibited a linear response over a wide range of 0-8 mM DIC, with a calculated LOD of 5 µM and a 90% response time of 150 s. The sensor was successfully tested in measuring DIC in bottled mineral water and seawater. This DIC microsensor holds the potential to become an important tool in environmental sensing and beyond for measurements of DIC at high spatial and temporal resolution.

Optode Based Chemical Imaging-Possibilities, Challenges, and New Avenues in Multidimensional Optical Sensing.

Seeing is believing, as the saying goes, and optical sensors (so-called optodes) are tools that can make chemistry visible. Optodes react reversibly and quickly (seconds to minutes) to changing analyte concentrations, enabling the spatial and temporal visualization of an analyte in complex environments. By being available as planar sensor foils or in the form of nano- or microparticles, optodes are flexible tools suitable for a wide array of applications. The steadily grown applications of in particular oxygen (O2) and pH optodes in fields as diverse as medical, environmental, or material sciences is proof for the large demand of optode based chemical imaging. Nevertheless, the full potential of this technology is not exhausted yet, challenges have to be overcome, and new avenues wait to be taken. Within this Perspective, we look at where the field currently stands, highlight several successful examples of optode based chemical imaging and ask what it will take to advance current state-of-the-art technology. It is our intention to point toward some potential blind spots and to inspire further developments.

Oxygen consumption of individual cable bacteria.

The electric wires of cable bacteria possibly support a unique respiration mode with a few oxygen-reducing cells flaring off electrons, while oxidation of the electron donor and the associated energy conservation and growth is allocated to other cells not exposed to oxygen. Cable bacteria are centimeter-long, multicellular, filamentous Desulfobulbaceae that transport electrons across oxic-anoxic interfaces in aquatic sediments. From observed distortions of the oxic-anoxic interface, we derived oxygen consumption rates of individual cable bacteria and found biomass-specific rates of unheard magnitude in biology. Tightly controlled behavior, possibly involving intercellular electrical signaling, was found to generally keep <10% of individual filaments exposed to oxygen. The results strengthen the hypothesis that cable bacteria indeed have evolved an exceptional way to take the full energetic advantages of aerobic respiration and let >90% of the cells metabolize in the convenient absence of oxidative stress.

Dynamic Sensor Concept Combining Electrochemical pH Manipulation and Optical Sensing of Buffer Capacity.

State-of-the-art electrochemical and optical sensors present distinct advantages and disadvantages when used individually. Combining both methodologies offers interesting synergies and makes it possible to exploit strengths and circumvent possible problems of the individual methods. We report a dynamic sensing concept for buffer capacity by applying water electrolysis to modulate the pH microenvironment in front of an optical pH sensor placed in a flow cell. Using this combinatory approach in a nonequilibrium readout mode allowed us to assess the concentration of different buffer species in relatively short time (1 min per measurement). Theoretical simulations of the system were performed to validate the presented method. Additionally, the dynamic measurement approach enabled in situ determination of the apparent pKa of MOPS (3-(N-morpholino)propanesulfonic acid) buffer at ambient conditions. The dynamic and combinatory approach presented here holds large potential also for other pH-active analytes.